1. Field of the Invention
The present invention relates to a three dimensional image processing apparatus which reconstructs a three dimensional image from a plurality of X-ray images obtained in different radiographing directions.
2. Description of the Related Art
Three dimensional image reconstruction processing is to be performed for a moving object, more specifically, for example, a cardiovascular vessel. Since the cardiovascular vessel moves, reconstructing its image by a conventional technique causes a large motion blur. The image quality of the reconstructed image is unsuitable for diagnosis. There have been proposed several countermeasure techniques for such a problem. For example, the position of a region on an image is corrected, and a three dimensional image is reconstructed from the corrected image.
This technique generates, for example, 200 images at different radiography angles. The operator selects several discrete key images from the 200 images. The operator manually designates anatomically characteristic regions (feature points) on the several key images. The system calculates the three dimensional coordinates of the feature points by geometric calculation from the designated feature points and the radiography angles. The system re-projects the three dimensional coordinates on the respective images the system also tracks the feature points for non-selected frames. The system corrects the shifts between the re-projected positions and the tracked positions.
This makes it possible to perform reconstruction processing upon performing image deformation to make the image look like stationary. The obtained reconstructed image is therefore a sharp image without any motion blur.
However, the operation which the operator performs to designate feature points accompanies arbitrariness. This arbitrariness makes the image quality of a reconstructed image unstable.
As shown in FIG. 1, for example, when images are disproportionally selected, numbers of frames NA, NB, and ND greatly vary. The tracking accuracy in the interval A is relatively low because number of tracking frames are large, and the tracking accuracy in the interval D is relatively high because number of tracking frames are small. The accuracy of position correction is low in the interval A, and the accuracy of position correction is high in the interval B. This degrades the image quality of a final reconstructed image. That is, the image quality of reconstructed images becomes unstable in accordance with the selection of images.